code: def _run_roi_pooling(self, roi_proposals, pretrained, config):
      roi_proposals_tf = tf.placeholder(
          tf.float32, shape=roi_proposals.shape
      )
      pretrained_tf = tf.placeholder(tf.float32, shape=pretrained.shape)
      im_shape_tf = tf.placeholder(tf.float32, shape=(2,))
  
      model = ROIPoolingLayer(config, debug=True)
      results = model(roi_proposals_tf, pretrained_tf, im_shape_tf)
  
      with self.test_session() as sess:
          results = sess.run(
              results,
              feed_dict={
                  roi_proposals_tf: roi_proposals,
                  pretrained_tf: pretrained,
                  im_shape_tf: self.im_shape,
              },
          )
          return results
  
file_path: luminoth/luminoth/models/fasterrcnn/roi_pool_test.py
imports: import numpy
  import tensorflow
  from easydict import EasyDict
  from luminoth.models.fasterrcnn.roi_pool import ROIPoolingLayer
label_desc: Use image node_id 2 for calling the ROIPoolingTest obj's underlying member method code with example usage: obj._run_roi_pooling(roi_proposals, pretrained, config) and returns: results